Algernon Sprint
/install algernon-sprint
algernon-sprint
You run a timed interleaved study sprint. Cards from all installed materials are shuffled together — interleaving different topics is the point, because it forces retrieval across contexts and strengthens long-term retention.
Constants
DB=/home/antonio/Documents/huyawo/estudos/vestibular/data/vestibular.db
Card Limits by Duration
| Duration | Max Cards |
|---|---|
| 15 min | 20 cards |
| 25 min | 35 cards |
| 45 min | 60 cards |
Step 1 — Plan the Sprint
Fetch due cards across all materials:
sqlite3 $DB \
"SELECT c.id, c.type, c.front, c.back, m.name as material
FROM cards c
JOIN card_state cs ON cs.card_id = c.id
JOIN decks d ON d.id = c.deck_id
JOIN materials m ON m.id = d.material_id
WHERE cs.due_date \x3C= date('now')
ORDER BY RANDOM()
LIMIT CARD_LIMIT;"
Interleave: shuffle so no two consecutive cards come from the same material. If there aren't enough due cards to fill the limit, use cards from the same material twice rather than having fewer than ~15 cards for a 25-min sprint.
Step 2 — Sprint Start
Display:
Sprint: [DURATION] minutes
Materials: [list of materials with at least one card]
Cards: [count]
AskUserQuestion: ["Start sprint"] Record start time.
Step 3 — Sprint Loop
Run the same card review flow as algernon-review:
- Flashcards: show front → reveal back → Again/Good
- Dissertative/Argumentative: show front → free-text answer → AI evaluate → Again/Good
- After each grade, run FSRS scheduling (see
algernon-reviewfor FSRS formulas)
After every 10 cards, display:
Cards remaining: N | Estimated time: X min
Step 4 — Post-Sprint Break
After all cards reviewed:
Sprint complete. Take a 5-minute break.
Cards reviewed: N | Session retention: X%
AskUserQuestion: ["Start post-sprint test"]
Step 5 — Post-Sprint Retrieval Test
Select 5 random cards from the cards reviewed in this sprint. For each card:
- Show only the front.
- AskUserQuestion: ["Show answer"] — then show the back.
- AskUserQuestion options: ["Again", "Good"]
- Run FSRS update with the new grade.
Display:
Post-sprint test complete.
Sprint retention: X%
Post-sprint retention: Y%
Session gain: +Z%
The gain metric shows whether the sprint improved retention above what FSRS predicted — a positive gain means the interleaved practice worked.
Step 6 — Save Memory
Append to today's conversation log:
[HH:MM] sprint [DURATION]min
Cards: N | Sprint retention: X% | Post-sprint: Y% | Gain: +Z%
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install algernon-sprint - 安装完成后,直接呼叫该 Skill 的名称或使用
/algernon-sprint触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Algernon Sprint 是什么?
Timed interleaved study sprint for OpenAlgernon. Use when the user runs `/algernon sprint [15|25|45]`, says "sprint de estudo", "sessao cronometrada", "25 mi... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 203 次。
如何安装 Algernon Sprint?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install algernon-sprint」即可一键安装,无需额外配置。
Algernon Sprint 是免费的吗?
是的,Algernon Sprint 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Algernon Sprint 支持哪些平台?
Algernon Sprint 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Algernon Sprint?
由 Antonio V. Franco(@antoniovfranco)开发并维护,当前版本 v1.0.0。